Results for “I-V” — Page 6

DOE OSTI2024

Contactless Production Testing of Silicon Solar Cells

Critical cost reductions in silicon solar cells are made by minimizing silver usage in their metal contacts. The reason why is both clear and unavoidable—silver is not only expensive, but also a potential limiting resource for scale-up (the PV industry alone used 10.3 % of the global silver supply in 2020 [1]). The result is solar cells with vanishing electrical contact area that are extremely difficult to test prior to module manufacture, when they must be sorted for quality to maximize power output and reliability of the subsequent modules. This project developed a new measurement instrument that enables the transition to solar cells with very low silver content, including cell designs with both minimal busbars and no busbars at all to electrically contact. The resulting instrument at project completion demonstrated the ability to sort cells with comparable—or better—results than existing technology. Compared to existing cell-test instruments, the new tool has minimal contacting requirements, which lowers the maintenance costs and use of consumable parts. We demonstrated innovative, yet pragmatic, solutions for reporting a comprehensive set of measurement results useful for both cell sorting (going forward in the line for module manufacture) and process control (looking backward in the line to identify cell manufacturing issues from wafer to cell-test). In addition to the traditional current-voltage characterization at cell test—short circuit current, open-circuit voltage, power, efficiency and fill factor—the new tool maintains all the advanced parameter characterization of our existing product line such as a substrate doping measurement, carrier recombination (lifetime) analysis, and surface recombination analysis.

14 SOLAR ENERGY↗

DOE OSTI2025

Comparing Outdoor to Indoor Performance for Bifacial Modules Affected by Polarization-Type Potential-Induced Degradation

Bifacial photovoltaic (PV) modules have the advantage of using light reflected off of the ground to contribute to power production. Predicting the energy gain is challenging and requires complex models to do so accurately. Often, module degradation over time is neglected in models for the sake of simplicity or is underestimated. Comparing outdoor and indoor current–voltage (I–V) performance for bifacial modules is more challenging than for monofacial modules, as there are additional variables to consider such as rear albedo non-uniformity, cell mismatch, and their effects on temperature. This challenge is compounded when heterogeneous degradation modes occur, such as polarization-type potential-induced degradation (PID-p). To examine the effects of PID-p on I–V predictions using an empirical data-driven approach, 16 bifacial PERC modules are installed outdoors on racks with different albedo conditions. A subset is exposed to high-voltage biases of −1500 V or +1500 V. Outdoor data are traced at irradiance ranges of 150–250 W/m 2 , 500–600 W/m 2 , and 900–1000 W/m 2 . These curves are corrected using control module temperature, wire resistivity, and module resistance measured indoors. We examine several methods to transform indoor I–V curves to accurately, and more simply than existing methods, approximate outdoor performance for bifacial modules without and with varying levels of PID-p degradation. This way, bifacial performance modeling can be more accessible and informed by fielded, degraded modules. Distributions of percent errors between indoor and outdoor performance parameters and Mean Absolute Percent Errors (MAPEs) are used to assess method quality. Results including low-irradiance data (150–250 W/m 2 ) are discussed but are filtered for quantifying method quality as these data introduce substantial errors. The method with the most optimal tradeoff between low MAPE and analysis simplicity involves measuring the front side of a module indoors at an irradiance equal to plane-of-array irradiance plus the product of module bifaciality and albedo irradiance. This method gives MAPE values of 1–6.5% for non-degraded and 1.6–5.9% for PID-p degraded module performance.

14 SOLAR ENERGY↗